
pmid: 31279169
One of the major complications that patients experience during pharmacological treatment is the occurrence of adverse drug reactions (ADRs). The most affected organs are the liver, kidney, heart and the gastrointestinal-immune system. In comparison to the other organs, less progress has been made on human-relevant prediction of drug-induced intestinal toxicity, evidencing current large data gaps. The most widely used drugs that are associated with intestinal damage include chemotherapeutics, such as 5-Fluorouracil or Tyrosine Kinase Inhibitors (TKIs), as well as non-steroidal anti-inflammatory drugs (NSAIDs). Chemotherapeutics are regarded as inducers of acute intestinal toxicity whereas NSAIDs are associated with chronic inflammation of the intestine. In view of the fact that only a few studies have been dedicated to studying cellular and genomic responses in relation to drug-induced intestinal ADRs, little is known about how intestinal toxicity develops after exposure to such drugs or which molecular mechanisms are involved. Therefore, new models and experiments are required to establish transcriptomic responses and alterations of molecular markers induced by different medicines. This review summarizes the available information about transcriptomic responses and biomarkers of toxicity induced by 5-FU, NSAIDS or TKIs in different experimental models. Future investigation should address the challenges in predicting intestinal toxicity induced by drugs and unveil specific gene expression profiles that can be applied in the development of safer drugs.
Intestinal Diseases, Anti-Inflammatory Agents, Non-Steroidal, Humans, Fluorouracil, Transcriptome, Protein Kinase Inhibitors
Intestinal Diseases, Anti-Inflammatory Agents, Non-Steroidal, Humans, Fluorouracil, Transcriptome, Protein Kinase Inhibitors
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 16 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
